Model Sync Pipeline

Two background services: one writes engineering data into 3D models, the other precomputes model descriptors to Blob Storage for the app to read.

• Azure Functions publish model change events onto Service Bus; Kubernetes workers consume the queue and scale on queue depth with KEDA.
• Explicit failure handling: exponential backoff, dead-lettering for permanent failures, and per-session locking so concurrent jobs cannot collide on one model.
• Pulls engineering data from REST APIs and writes it into models as native elements, so project data is visible against the design.

• TypeScript
• Kubernetes
• KEDA
• Azure Service Bus